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--- |
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base_model: meta-llama/Llama-2-13b-hf |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: radiopaedia-inst_240215-llama2_13b-240215 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# radiopaedia-inst_240215-llama2_13b-240215 |
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This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7504 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.851 | 0.05 | 20 | 0.8541 | |
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| 0.8377 | 0.11 | 40 | 0.8270 | |
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| 0.795 | 0.16 | 60 | 0.8237 | |
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| 0.7699 | 0.21 | 80 | 0.8089 | |
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| 0.953 | 0.27 | 100 | 0.7974 | |
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| 0.6894 | 0.32 | 120 | 0.7884 | |
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| 0.8883 | 0.37 | 140 | 0.7836 | |
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| 0.8814 | 0.42 | 160 | 0.7792 | |
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| 0.8322 | 0.48 | 180 | 0.7668 | |
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| 0.783 | 0.53 | 200 | 0.7745 | |
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| 0.6963 | 0.58 | 220 | 0.7683 | |
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| 0.7508 | 0.64 | 240 | 0.7540 | |
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| 0.7326 | 0.69 | 260 | 0.7582 | |
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| 0.7751 | 0.74 | 280 | 0.7501 | |
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| 0.6995 | 0.8 | 300 | 0.7473 | |
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| 0.7759 | 0.85 | 320 | 0.7428 | |
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| 0.6506 | 0.9 | 340 | 0.7383 | |
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| 0.7285 | 0.96 | 360 | 0.7296 | |
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| 0.5833 | 1.01 | 380 | 0.7347 | |
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| 0.5223 | 1.06 | 400 | 0.7535 | |
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| 0.3866 | 1.12 | 420 | 0.7685 | |
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| 0.4375 | 1.17 | 440 | 0.7586 | |
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| 0.4582 | 1.22 | 460 | 0.7539 | |
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| 0.4946 | 1.27 | 480 | 0.7646 | |
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| 0.5255 | 1.33 | 500 | 0.7670 | |
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| 0.4355 | 1.38 | 520 | 0.7581 | |
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| 0.4287 | 1.43 | 540 | 0.7574 | |
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| 0.478 | 1.49 | 560 | 0.7602 | |
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| 0.4236 | 1.54 | 580 | 0.7590 | |
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| 0.4873 | 1.59 | 600 | 0.7602 | |
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| 0.5377 | 1.65 | 620 | 0.7582 | |
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| 0.4546 | 1.7 | 640 | 0.7556 | |
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| 0.444 | 1.75 | 660 | 0.7539 | |
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| 0.3584 | 1.81 | 680 | 0.7526 | |
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| 0.4446 | 1.86 | 700 | 0.7502 | |
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| 0.385 | 1.91 | 720 | 0.7506 | |
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| 0.5061 | 1.97 | 740 | 0.7504 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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